myGwork - LGBTQ+ Business Community · 3 days ago

Senior Data Scientist

North Carolina, United States

Full-time

Remote

Senior Level

3+ years exp

Wonder how qualified you are to the job?

Maximize your interview chances

Internet

Insider Connection @myGwork - LGBTQ+ Business Community

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Design, develop, and deploy generative models for various applications with a focus on text generation and semantic entity extraction.

Collaborate with stakeholders to identify business needs, define project scopes, and establish data-driven solutions.

Mentor junior data scientists/interns, providing guidance on best practices and industry standards.

Stay up to date with the latest research and advancements in Generative AI and related fields.

Collaborate with other teams, such as engineering and product management, to integrate models into production environments.

Establish and maintain documentation for models, algorithms, and processes.

Ensure all projects meet quality, performance, and security standards.

Communicate sophisticated concepts and findings effectively to both technical and non-technical audiences.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data ScienceMachine LearningGenerative AIAI AlgorithmsML FrameworksRegression ModelsStatsmodelsTime Series ForecastingGBMXgBOOSTCloud SolutionsMLOps PipelinesAWSMS AzureMLOps FrameworksKubeflowMLFlowDataRobotAirflowDockerKubernetesDeep LearningProbabilistic ModelingPyTorchTensorflowScikit-learnKerasData PipelinesData Processing SystemsCloud Platforms

Required

Master's degree in Computer Science, Statistics, Mathematics, or a related field.

Minimum of 3 years as a Data Scientist or Machine Learning Engineer, with expertise in Generative AI.

Experience implementing AI/data science algorithms using modern ML frameworks (e.g. Regression Models, Statsmodels, Time Series Forecasting, GBM, XgBOOST etc).

Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure).

Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc. some experience with Docker and Kubernetes.

Solid background in machine learning, deep learning, and probabilistic modeling.

Proficiency in data science tools and frameworks, such as PyTorch, Tensorflow, Scikit-learn, and Keras.

Experience designing and implementing large-scale data pipelines and processing systems.

Familiarity with cloud platforms (AWS & Azure) and containerization technologies (Docker, Kubernetes).

Strong programming skills in Python and experience working with version control systems (Git).

Superb communication and teamwork skills.

Experience mentoring junior colleagues and interns.